Changes to my Website

Overall Changes I Made to my Website

• Substantially improved my citations
  
• Added notes within my code to make it clearer
• Added code folding to all projects and overall cleaned up the presentation
• Edited introductions so they had a professional tone and appearance
• Adjusted home page to describe my current skills and career interests
• Added Resume

Creating a new Simulation

• Initially created a simulation about my odds to receive a single.
  • Insufficient information and an overload of variables hindered simulation value
  • Additionally overall lack of clarity throughout project
• Instead I chose to get a better understanding of the Pomona Baseball teams success

Leading Question

• Is Pomona truly underperforming the year after a historic run?
  • 2022 historic run to regionals
  • 2023 poor season and missed SCIAC playoffs
  • 2024 greatest run in history to NCAA World Series in Cleveland
  • 2025 sentiments of a let down season (although ended up finishing strong)

Collecting the Data and Simulating the Season

• Utilized Massey Ratings to collect winning percentages https://masseyratings.com/cbase2024/ncaa-d3/ratings

# A tibble: 14 × 5
   team             win_prob games  wins losses
   <chr>               <dbl> <dbl> <int>  <dbl>
 1 CMS                  0.56     3     1      2
 2 La Verne             0.55     4     1      3
 3 ETBU                 0.53     3     1      2
 4 Occidental           0.85     3     2      1
 5 Cal Lu               0.6      3     2      1
 6 Cal Tech             0.95     3     2      1
 7 Whittier             0.84     4     2      2
 8 Lewis and Clark      0.71     3     2      1
 9 Pacific Lutheran     0.73     2     1      1
10 Chapman              0.6      3     1      2
11 Redlands             0.74     3     2      1
12 MIT                  0.8      2     1      1
13 UW La Crosse         0.54     1     1      0
14 Tufts                0.65     3     2      1

Massey Ratings

https://masseyratings.com/game.php?s0=614639&oid0=6286&h=0&s1=614639&oid1=0

Results of 1,000 Simulations

• After mapping the simulation 1,000 times I found the following basic stats:

set.seed(42)  # for reproducibility

#  original schedule
schedule <- data.frame(
  team = c("CMS", "La Verne", "ETBU", "Occidental", "Cal Lu", "Cal Tech", "Whittier",
           "Lewis and Clark", "Pacific Lutheran", "Chapman", "Redlands", 
           "MIT", "UW La Crosse", "Tufts"),
  win_prob = c(0.56, 0.55, 0.53, 0.85, 0.60, 0.95, 0.84,
               0.71, 0.73, 0.60, 0.74, 
               0.80, 0.54, 0.65),
  games = c(3, 4, 3, 3, 3, 3, 4,
            3, 2, 3, 3,
            2, 1, 3)
)

# simulation function
simulate_season <- function(schedule) {
  results <- schedule |>
    rowwise() |>
    mutate(
      wins = sum(runif(games) < win_prob),
      losses = games - wins
    ) |>
    ungroup()
  
  total_wins <- sum(results$wins)
  total_losses <- sum(results$losses)
  
  tibble(total_wins = total_wins, total_losses = total_losses)
}

# Run simulation 1000 times
n_simulations <- 1000
sim_results <- map_dfr(1:n_simulations, ~simulate_season(schedule))

# Summary
summary_stats <- sim_results |>
  summarise(
    avg_wins = mean(total_wins),
    sd_wins = sd(total_wins),
    median_wins=median(total_wins),
    max_wins = max(total_wins),
    min_wins = min(total_wins)
  )


print(summary_stats)

# A tibble: 1 × 5
  avg_wins sd_wins median_wins max_wins min_wins
     <dbl>   <dbl>       <dbl>    <int>    <int>
1     27.7    2.78          28       36       19

Graphical Presentation

• Created a shiny bar graph

https://nicols18.shinyapps.io/simulation/

Conclusions

• Final result of 27 wins aligns closely with the center of the simulated distribution.

• Slightly underperformed vs. expected average (27.7) and median (28), but the difference is minimal.

• Performance is respectable, not disappointing—especially when considering predictions were based on the historic 2024 season.

• In 2024, the team won 30 games, yet was predicted for 28—overperformed even with elite stats.

Will Pomona get a Regional Bid?

• Guaranteed bid if they win SCIAC Playoffs starting today at 3pm
• Top 23 teams in terms of NPI that do not win their conference get an at large bid
• 64 total teams make the playoffs
• NPI has a final calculation on May 11th
• Pomona is currently 54th nationally in NPI. Will they get a bid?